This stands in a stark contrast to the reconstruction perceptual or feature-matching losses commonly used in conditional layout-to-image approaches [1]}, [2]}, [3]}, which, unjustifiably, compare the appearance of a newly generated image \(X\)  to that of a natural source image \(X^{\prime }\)  (mathematically, through either \(\mathcal {L}_{P}(X,X^{\prime })\)  or \(\mathcal {L}_{FM}(f(X),f(X^{\prime }))\) ), even though there is no reason for them to be similar in terms of style and texture, beyond sharing the same layout. Consequently, those losses severely and fundamentally hinder the diversity of the generated scenes (as shown in section ). We circumvent this deficiency by comparing instead the layout implied by the new image with the source layout it is meant to follow, thereby staying true to the original objective of the translation task.
